For Heads-of · Practitioner
Output validation and guardrails
Deterministic schema validation and sanitisation of AI-generated output before it reaches any downstream system.
- preventive
- output-handling
- validation
What it does
Schema-validates and sanitises AI-generated output deterministically before it reaches any downstream system or user.
Where it fits
The output-side counterpart to input validation — treats model output as untrusted until proven otherwise.
Risks this mitigates
The risks this control addresses, ranked by effectiveness.
Prompt injection
Attacker-controlled input overrides system instructions, either directly or via retrieved/tool content treated as trusted.
Sensitive information disclosure
A model surfaces training, fine-tuning, or retrieval-sourced sensitive data in its output.
Improper output handling
AI-generated output is passed to a downstream interpreter, renderer, or system call without validation, enabling injection-style attacks beyond the model itself.
Hidden context exposure
Content the operator assumed was hidden from the user, such as retrieval context, RAG schemas, or policy logic, is exposed or inferred through the model, beyond just the system prompt.